Coupling Suspended Sediment Dynamics and Light Penetration in the Upper

Chesapeake Bay

Charles L. Gallegos

Smithsonian Environmental Research Center

Photos by Grace Cartwright

Outline• Review

• Model Refinement

• Field Work–Potomac findings

–Baywide extension

• Summary

Elements of Radiative Transfer Modeling in Natural Waters

• Radiative Transfer Equations perform an energy balance on an infinitesimal solid angle, accounting for gains and losses

• First-order effects are governed by the magnitude of inherent optical properties (IOPs): absorption coefficient, scattering coefficient, and scattering phase function (principally, backscattering:total scattering ratio)

• Primary water quality determinants of the IOPs are colored dissolved organic matter (CDOM), phytoplankton pigments, and other particulates (detritus, suspended minerals).

Inherent Optical Properties

esParticulat algal-NonPhytoCDOMwatertotal aaaaa

Absorption Coefficient

•Water: From published tables (Pope and Fry 1997)

Laboratory

In Situ (total-water)•WETLabs Spectral ac-9

•CDOM: Spectrophotometric with long path cell•Particulate: Filter pad method

Inherent Optical Properties

tp acb Particulate Scattering

Beam Attenuation

Total Absorption

Scattering Coefficient

Also measured using WETLabs ac-9 in situ or in laboratory.

Inherent Optical PropertiesScattering Phase Function, ()/b

• Probability distribution of scattered photons

• Strongly peaked in the forward direction

• Well specified by the ratio of backscattering:total scattering, bb/b

• Measured in situ by HOBILABS Hydroscat-6 or WETLabs ECO-VSF-3

Backscattering,

bb

Forward scattering,

bf

bf

bf

bb

bbb

Kd Relationship Revisited:Parameterize effects of variations in…

• Solar incidence angle, µ0

• Relative proportion of scattering and absorption, principally b:a ratio

• Backscattering ratio, bb:b

• Optical depth, c·z

• Direct and diffuse incident light*--New complexity

New Bio-optical Model is Based On*:

0 b

zd

baK

Depends on: optical depth, backscattering ratio, solar zenith angle, and scattering:absorption ratio.

Ratio backscattering:total scattering

Cosine in-water solar zenith angle

*—Albert, A., and C. D. Mobley. 2003. An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters. Optics Express 11: 2873-2890.

Implementation

• Algorithm has 33 equations due to multiple dependencies of z on other parameters (i.e. bb/b, b/a, etc.)

• Some of the governing parameters, e.g. backscatter ratio, are poorly represented in data

• Solution at each cell and time step would place excessive drag on complete model

Look-up Table Approach• Used bio-optical model to generate Kd values for

a range of inherent optical properties in nested loops of:– I: Cosine solar angle (8 bins, 0.71-0.91)– J: CDOM (20 bins, 0.1-8 m-1)– K: Chlorophyll absorption (35 bins, 0.02-18.4 m-1)– L: Particulate scattering (35 bins, 0.6-570 m-1)– M: Particulate absorption:scattering ratio (10 bins,

0.06-0.24)

• Resulting array consists of 1,960,000 values of Kd(PAR)

Lookup Table Approach cont’d.

• Initialize:– Read in Kd(PAR) array

– Read in season- and segment-specific inherent optical properties

• From date, segment, and water quality (CDOM, chlorophyll & TSS), search bins to find I, J, K, L, & M

• Look up Kd(PAR) in array

Lookup Table Approach cont’d.Must Determine…

• Absorption by CDOM• Absorption by chlorophyll

– Product of specific-absorption coefficient and chlorophyll concentration

• Scattering by particulates– Product of specific-scattering coefficient and TSS

concentration

• Absorption by non-algal particulates– Product of scattering and absorption:scattering ratio

Need: CDOM absorption, and specific-absorption and –scattering coefficients on segment and season basis

CDOM Concentrations: Potomac

0 20 40 60 80 100 120 1400.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

Distance Below Fall Line (km)

ag(4

40

) (m

-1)

Mar04 Jun04 Aug04 Mar05 Jun05 Sep05

• Seasonal variability>>Spatial

• Current sampling program expected to be adequate characterization

Bay-wide Extension: Sample Coverage

CDOM Absorption: Bay-wide

Chlorophyll-specific Absorption: Potomac

0 2 4 6 8 10 12 14 16 180.0

0.1

0.2

0.3

0.4

0.5

a (6

75)

(m-1

)

Chlorophyll (mg m-3)

March June Aug-Sep

a*(675) = 0.028 m2 mg-1 Mar-Jun

0.018 m2 mg-1 Aug-Sep

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.0902468

101214161820222426283032

Fre

quen

cya

*(675) m2 (mg Chl)-1

Ensemble mean: 0.030 m2 mg-1

Forced zero-intercept Regressions

*Point-estimate a(675)/[Chla]

*—Necessary when sample size is small

Chlorophyll-specific Absorption: Bay-wide

Particulate Scattering: Potomac

0 50 100 150 200 250

0

20

40

60

80

100

120

bp(5

55)

(m-1)

TSS (g m-3)

Mar JunAug-Sep

20 40 60 80 100 1200.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

b p* (555

) (m

2 g-1)

km Below Fall Line

•Forced zero-intercept: = 0.57 m2 g-1

•Ensemble average of point-estimates = 0.94 m2 g-1

•Varies systematically along river axis

Particulate Scattering: Bay-wide

NAP Absorption:Scattering Ratio: Potomac

0 2 4 6 8 1012141618202224262830323436380.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

a p-(

440)

(m

-1)

bp(555) (m-1)

Mar Jun Aug-Sep

555

440

p

p

b

aPCI Define “Particle Color Index”, PCI,

•From forced zero-intercept regression, PCI=0.088

•Ensemble average, PCI=0.12

•Variability principally temporal

2 3 4 5 6 7 8 9 100.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

PC

I

Month

NAP Absorption:Scattering Ratio: Bay-wide

Light Attenuation Model EvaluationBased on Measured Coefficients—Potomac River

0 1 2 3 4 50

1

2

3

4

5

Sim

ulat

ed K

d(P

AR

) (m

-1)

Measured Kd(PAR) (m-1)

• 2004 data

• Slope (model vs. obs.) = 0.98, r2=0.75

• Used measured, station-averaged coefficients

Light Attenuation ModelBay-wide Extension Based on Look-up Table Approach

1 10

1

10

Model Ref Reps

Mod

eled

Kd(

PA

R)

(m-1)

Measured Kd(PAR) (m-1)Chesapeake Bay Program Data

5,873 Observations

1995-1999

Backscatter Fraction: Potomac

8 8

3 2 22 2

2 35

3 3 3

LE2.

3

LE2.

2

PR

01

PR

02

PR

03

PR

04

PR

05

PR

06

PR

07

PR

08

PR

09

PR

10

PR

11

0.000

0.005

0.010

0.015

0.020

0.025

Bac

ksca

tter

Fra

ctio

n, b

b/b

Station

• Difficult to measure in RET/TF sections of river due to high concentrations of TSS saturating instrument

• Available data indicates systematic longitudinal gradient

• Direct measurements unavailable elsewhere, except CB4MH (average=-.0125)

LE2.

3

LE2.

2

PR

01

PR

02

PR

03

PR

04

PR

05

PR

06

PR

07

PR

08

PR

09

PR

10

PR

11

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

Pre

dic

ted

Kd(P

AR

) (m

-1)

Station

Implications for Prediction of Kd(PAR)

Constant Water Quality Assumed:

CDOM=0.5 m-1; Chla=6 mg m-3; TSS=12.7 g m-3; based on 6/15/05, PR04

• Ca. 30% change in simulated Kd(PAR) due to changes in bb/b alone

• For assumed condition, change crosses SAV Tier II habitat requirement

To Do

• Re-generate Kd for Lookup Table varying backscatter ratio, bb/b

• Modify Lookup Table routine to take advantage of further bb/b data as it becomes available

Symbols for diagrams courtesy of the Integration and Application Network (ian.umces.edu/symbols), University of Maryland Center for Environmental Science.